Gérard Scemama

Simulating the impact of future Internet on multimodal mobility

In the context of the EC-funded project Instant Mobility, we have defined a comprehensive architecture for transport and mobility applications that aim to innovate by introducing future Internet technologies to this domain. We have defined an Internet-based “multimodal travel platform” that provides information and services able to support new types of connected transport applications. The considered scenario is centered on multimodal travelers (both drivers and passengers). In this paper, we present the SM4T1 simulator, that we have designed and implemented to test the platform and to interact with it on behalf of multimodal travelers. SM4T is a fully agent-based simulator for multimodal travelers mobility. The application simulates the movements of travelers on the different transport networks (road and public transport) while taking into account the changes in travel times and the status of the networks.

Agent-based coordination model for designing transportation applications

This paper presents an environment-centered approach to design multi-agent solutions to transportation problems. Based on the property-based coordination principle (PbC), the objective of our approach is to solve three recurrent issues in the design of these solutions: the knowledge problem, the space-time dimension and the dynamics of the real environment. To demonstrate the benefits of our approach, two completely different applications, a demand-responsive transportation system and a simulator for crisis management, both based on this principle are presented. For each of them, we show how these recurrent issues have been solved.

Impact of Travelers Information Level on Disturbed Transit Networks: A Multiagent Simulation

With the generalization of real-time traveler information, the behavior of modern transport networks becomes harder to analyze and to predict. It is now critical to develop simulation tools for mobility policies makers, taking into account this new information environment. Information is now individualized, and the interaction of a population of individually guided travelers have to be taken into account in the simulations. Multiagent simulation is proving to be a powerful model for analyzing transport activities. Indeed, autonomous agents provide an appropriate basis for modeling heterogeneous systems and environment-based systems. In this paper, we present a multiagent simulation model to measure the impact of information provision on the quality of passengers travels. This impact is measured by simulating different scenarios in function of the percentage of connected travelers, represented as agents. These simulated scenarios are analyzed following their impact on the average travel times of the travelers. Results show that the number of connected travelers has a positive impact on overall travel times up until a certain threshold before becoming negative.

A Data-Oriented Coordination Language for Distributed Transportation Applications

Data-oriented coordination languages rely on a shared space in which agents add, read and retrieve data. They are intuitively well suited for distributed transportation applications, where different actors evolve in a highly dynamic and very constrained environment. However, existing coordination languages can hardly be used for transportation applications, because they cannot express agents complex interaction needs. Indeed, in transportation applications, the interaction needs of the agents are driven by their current context and by ambient conditions, expressed in the form of constraints on the values taken by variables. In this paper, we propose Lacios , a new data-oriented coordination language for designing and implementing distributed transportation applications, and we illustrate our proposal with two examples: a traveler information system and a demand-responsive transport system. Lacios allows agents to express complex interaction needs, including agents states, system objects values, operators and functions, and is grounded on a model where the multi-agent system design is centered on the environment.

Building a Realistic Data Environment for Multiagent Mobility Simulation

Transport systems are increasingly complex and are made of more and more connected entities. It becomes critical to develop micro-simulation tools to understand the new transport systems dynamics. However, the data for building mobility simulation are quite hard to get, and simulations on new areas are not easy to set up. In this paper, we propose methods for building a realistic data environment for multimodal mobility simulators. We also propose a method to integrate travel patterns (patterns of travelers’ origins and destinations). The methods presented in this paper can be used when dealing with new areas for which we have few and incomplete data.

Patterns to distribute mobility simulations

Travelers mobility simulation is a powerful tool to test strategies in a virtual environment, without impacting the quality of the real traffic network. However, existing mobility multiagent and micro-simulations can only consider a sample of the real volumes of travelers, especially for big regions. With distributed simulations, it would be easier to analyze and predict the status of nowadays networks. This kind of simulations requires big computational power and methods to split the simulation between several machines. This work describes how to achieve such a distribution in a microscopic simulation context, and compare our results with a previous work on macroscopic simulation.